Load Necessary Libraries

Data Import

See GitHub_Export/Documentation for information on provided data.

##   X Sub_ID     Cond   Avg_RPE    Avg_HR    SD_HR Max_HR Min_HR
## 1 1    1.1  Control  6.000000  73.06299 5.451750     87     63
## 2 2    1.2    Light 10.727273 106.34472 3.390666    114     98
## 3 3    1.3 Vigorous 16.818182 144.58533 4.232497    153    131
## 4 4    2.1 Vigorous 12.909091 152.13833 3.207753    158    145
## 5 5    2.2  Control  6.000000  88.95515 3.435594    101     81
## 6 6    2.3    Light  8.818182 116.47595 2.769795    126    108
##   Percentage_Time_In_Zone Avg_Lower_THR Avg_Upper_THR HR_reserve
## 1                      NA            NA            NA      128.5
## 2               0.9154472        100.55       112.115      128.5
## 3               0.8245614        139.10       150.665      128.5
## 4               0.9083333        145.98       156.627      118.3
## 5                      NA            NA            NA      118.3
## 6               0.9568823        110.49       121.137      118.3
##   Age_Predict_Max_HR    SD_RPE Mean_Percent_HRR SD_Percent_HRR
## 1              190.5 0.0000000         8.609332       4.242607
## 2              190.5 1.1037127        34.509506       2.638650
## 3              190.5 0.9816498        64.268737       3.293772
## 4              193.3 0.3015113        65.205692       2.711541
## 5              193.3 0.0000000        11.796407       2.904137
## 6              193.3 0.4045199        35.059978       2.341331
##   Accuracy_Response_Trials Accuracy_All_Trials No_Response   Max_RT    Min_RT
## 1                0.5789474                0.55           1 3.690534 1.1105052
## 2                0.8000000                0.80           0 2.627786 1.1844439
## 3                0.9000000                0.90           0 3.536698 1.5426400
## 4                0.9500000                0.95           0 2.520927 1.3734756
## 5                0.8500000                0.85           0 3.058130 1.0881356
## 6                0.9000000                0.90           0 2.148315 0.8554969
##    Mean_RT High_Confidence_Hit Low_Confidence_Hit Low_Confidence_Miss
## 1 2.425303                   9                  2                   2
## 2 1.852897                  16                  0                   0
## 3 2.197293                  17                  1                   1
## 4 2.063796                  18                  1                   1
## 5 1.709206                  14                  3                   0
## 6 1.414585                  16                  2                   2
##   High_Confidence_Miss HCH_percent LCH_percent LCM_percent HCM_percent
## 1                    6   0.4736842   0.1052632   0.1052632   0.3157895
## 2                    4   0.8000000   0.0000000   0.0000000   0.2000000
## 3                    1   0.8500000   0.0500000   0.0500000   0.0500000
## 4                    0   0.9000000   0.0500000   0.0500000   0.0000000
## 5                    3   0.7000000   0.1500000   0.0000000   0.1500000
## 6                    0   0.8000000   0.1000000   0.1000000   0.0000000
##        Seed RawScore ItmCnt DateFinished Computed.Score
## 1  41.51562       20     24     44515.43           9.61
## 2 299.50000       20     24     44517.40           9.09
## 3 305.84375       19     24     44522.40           9.88
## 4 305.45312       20     24     44529.43           9.38
## 5  39.46875       20     24     44531.41           9.47
## 6  39.15625       20     24     44538.41           9.49
##   Uncorrected.Standard.Score Age.Corrected.Standard.Score
## 1                        113                          116
## 2                        108                           99
## 3                        116                          127
## 4                        111                          103
## 5                        112                          108
## 6                        112                          108
##   National.Percentile..age.adjusted. Fully.Corrected.T.score Appointment_Number
## 1                                 85                      59                  1
## 2                                 48                      47                  2
## 3                                 96                      68                  3
## 4                                 57                      51                  1
## 5                                 71                      55                  2
## 6                                 71                      55                  3
##   pre_cc_mean pre_CE_mean pre_CO_mean pre_OE_mean post_CC_mean post_CE_mean
## 1    796.4958    783.5385    744.7333          NA     779.9412     979.1818
## 2    797.4454    679.1250    839.8500          NA     786.5378     946.1250
## 3    808.3077    764.4545    827.7059       895.5     800.7650     945.0000
## 4    856.0084    858.6667    848.7083      1181.0     858.2616     985.3333
## 5    835.9153    772.8571    831.9048      1276.0     834.4703     899.5714
## 6    783.9328    727.7500    785.5000          NA     780.8992     882.7500
##   post_CO_mean post_OE_mean commission_rate commission_rate_q1
## 1     850.8889           NA         0.40625          0.1428571
## 2     851.7619           NA         0.25000          0.0000000
## 3     855.0000          662         0.34375          0.2857143
## 4     823.2692           NA         0.09375          0.1428571
## 5     820.0909         1084         0.21875          0.1428571
## 6     786.8000           NA         0.12500          0.0000000
##   commission_rate_q2 commission_rate_q3 commission_rate_q4 omission_rate
## 1                0.4              0.750          0.2857143   0.000000000
## 2                0.4              0.250          0.2857143   0.000000000
## 3                0.4              0.250          0.4285714   0.007490637
## 4                0.1              0.125          0.0000000   0.003745318
## 5                0.3              0.250          0.1428571   0.003745318
## 6                0.2              0.000          0.2857143   0.000000000
##   omission_rate_q1 omission_rate_q2 omission_rate_q3 omission_rate_q4   meanRT
## 1       0.00000000                0       0.00000000                0 792.9326
## 2       0.00000000                0       0.00000000                0 796.4494
## 3       0.02941176                0       0.00000000                0 808.7094
## 4       0.00000000                0       0.01492537                0 856.2744
## 5       0.00000000                0       0.01492537                0 835.9323
## 6       0.00000000                0       0.00000000                0 782.9775
##   meanRT_q1 meanRT_q2 meanRT_q3 meanRT_q4    STD_RT STD_RT_q1 STD_RT_q2
## 1  752.4559  829.1538  801.4179  790.3881 117.44406  92.57356 122.17230
## 2  807.2794  778.9538  803.4328  795.4478 112.66725  93.16265 128.62244
## 3  791.3485  815.6308  838.9403  788.8657 126.92259  93.93263 125.66306
## 4  819.0147  870.9231  912.2273  824.7612  94.49642  72.27322  85.49768
## 5  824.5735  795.6308  892.4848  830.8507  95.27931  93.62267  65.09718
## 6  772.0441  805.2923  746.0448  809.3582  78.60183  65.80760  66.77077
##   STD_RT_q3 STD_RT_q4     CV_RT   CV_RT_q1   CV_RT_q2  CV_RT_q3   CV_RT_q4
## 1 138.94616 100.25527 0.1481136 0.12302855 0.14734575 0.1733754 0.12684310
## 2 128.03873  97.16158 0.1414619 0.11540323 0.16512203 0.1593646 0.12214703
## 3 137.48971 140.90970 0.1569446 0.11869945 0.15406857 0.1638850 0.17862318
## 4  99.13795  89.45798 0.1103576 0.08824410 0.09816904 0.1086768 0.10846531
## 5 109.15314  82.17097 0.1139797 0.11354071 0.08181833 0.1223025 0.09889980
## 6  97.23159  63.41917 0.1003884 0.08523813 0.08291494 0.1303294 0.07835736
##   error_rate error_rate_q1 error_rate_q2 error_rate_q3 error_rate_q4
## 1 0.04347826    0.01333333    0.05333333    0.08000000    0.02702703
## 2 0.02675585    0.00000000    0.05333333    0.02666667    0.02702703
## 3 0.04347826    0.05333333    0.05333333    0.02666667    0.04054054
## 4 0.01337793    0.01333333    0.01333333    0.02666667    0.00000000
## 5 0.02675585    0.01333333    0.04000000    0.04000000    0.01351351
## 6 0.01337793    0.00000000    0.02666667    0.00000000    0.02702703
##   mean_trial_length   dprime criterion Overall.Accuracy Total.Trials
## 1          801.1833 3.136054 1.3308249        0.8402778          144
## 2          801.1700 3.573342 1.1121810        0.8819444          144
## 3          801.0800 2.835082 1.0152907        0.8819444          144
## 4          801.1600 3.992217 0.6780977        0.9166667          144
## 5          804.5300 3.450628 0.9488922        0.8680556          144
## 6          805.3367 4.049201 0.8742512        0.8888889          144
##   Total.Trials.with.Response Total.Correct.Trials Lure.count Foil.count
## 1                        136                  121         23         93
## 2                        142                  127         23         95
## 3                        142                  127         23         95
## 4                        142                  132         23         96
## 5                        144                  125         24         96
## 6                        144                  128         24         96
##   Target.count Average.Response.Time Average.RT.L Average.RT.F Average.RT.T
## 1           20             1143.3596     1278.109    1033.7710     1497.985
## 2           24             1077.9169     1238.426     997.4947     1242.433
## 3           24             1077.9169     1238.426     997.4947     1242.433
## 4           23             1300.7063     1353.713    1287.9927     1300.765
## 5           24              988.5486     1095.612     928.2656     1122.617
## 6           24              855.3549     1030.025     774.8458     1002.721
##   Average.RT.when.Correct   TO_rate    TS_rate TN_rate   LO_rate   LS_rate
## 1               1118.1570 0.9000000 0.10000000       0 0.2173913 0.7826087
## 2               1042.6780 0.9166667 0.08333333       0 0.2173913 0.7391304
## 3               1042.6780 0.9166667 0.08333333       0 0.2173913 0.7391304
## 4               1298.4053 1.0000000 0.00000000       0 0.3043478 0.6521739
## 5                966.5344 0.9166667 0.08333333       0 0.4166667 0.5000000
## 6                828.1523 1.0000000 0.00000000       0 0.3333333 0.5416667
##      LN_rate    FO_rate    FS_rate   FN_rate    NR_rate  L3O_rate  L3S_rate
## 1 0.00000000 0.03225806 0.05376344 0.9139785 0.05555556 0.0000000 1.0000000
## 2 0.04347826 0.00000000 0.07368421 0.9263158 0.01388889 0.0000000 1.0000000
## 3 0.04347826 0.00000000 0.07368421 0.9263158 0.01388889 0.0000000 1.0000000
## 4 0.04347826 0.00000000 0.02083333 0.9791667 0.01388889 0.0000000 0.8333333
## 5 0.08333333 0.00000000 0.05208333 0.9479167 0.00000000 0.0000000 0.7142857
## 6 0.12500000 0.02083333 0.03125000 0.9479167 0.00000000 0.1666667 0.5000000
##    L3N_rate  L2O_rate  L2S_rate   L2N_rate  L1O_rate  L1S_rate   L1N_rate
## 1 0.0000000 0.2500000 0.7500000 0.00000000 0.3333333 0.6666667 0.00000000
## 2 0.0000000 0.1666667 0.8333333 0.00000000 0.3636364 0.5454545 0.09090909
## 3 0.0000000 0.1666667 0.8333333 0.00000000 0.3636364 0.5454545 0.09090909
## 4 0.1666667 0.3750000 0.6250000 0.00000000 0.4444444 0.5555556 0.00000000
## 5 0.2857143 0.5000000 0.5000000 0.00000000 0.6363636 0.3636364 0.00000000
## 6 0.3333333 0.3333333 0.5833333 0.08333333 0.5000000 0.5000000 0.00000000
##   Average.RT.when.incorrect Lure.Discrimination.Index
## 1                  1346.660                 0.7288453
## 2                  1376.273                 0.6654462
## 3                  1376.273                 0.6654462
## 4                  1331.080                 0.6313406
## 5                  1133.379                 0.4479167
## 6                  1072.975                 0.5104167
##   Lure.Discrimination.Index.Lure.Bin.3 Lure.Discrimination.Index.Lure.Bin.2
## 1                            0.9462366                            0.6962366
## 2                            0.9263158                            0.7596491
## 3                            0.9263158                            0.7596491
## 4                            0.8125000                            0.6041667
## 5                            0.6622024                            0.4479167
## 6                            0.4687500                            0.5520833
##   Lure.Discrimination.Index.Lure.Bin.1 Pattern.Completion.Rate
## 1                            0.6129032               0.1851332
## 2                            0.4717703               0.2173913
## 3                            0.4717703               0.2173913
## 4                            0.5347222               0.3043478
## 5                            0.3115530               0.4166667
## 6                            0.4687500               0.3125000
##   Recognition.Memory cortisol_t1 cortisol_t2 cortisol_t3 SedTimeTypDay
## 1          0.8677419          NA          NA          NA           480
## 2          0.9166667          NA          NA          NA           480
## 3          0.9166667          NA          NA          NA           480
## 4          1.0000000       0.505       0.412       0.484           480
## 5          0.9166667       0.582       0.474       0.376           480
## 6          0.9791667       0.759       0.603       0.470           480
##   WalkTimeTotMin ModTimeTotMin VigTimeTotMin Age HtIn      HtM     WtKg Wtlbs
## 1       30.00000     17.142857       5.00000  25 63.5 1.612903 58.27664 128.5
## 2       30.00000     17.142857       5.00000  25 63.5 1.612903 58.27664 128.5
## 3       30.00000     17.142857       5.00000  25 63.5 1.612903 58.27664 128.5
## 4       25.71429      6.428571      12.85714  21 65.7 1.668783 65.26077 143.9
## 5       25.71429      6.428571      12.85714  21 65.7 1.668783 65.26077 143.9
## 6       25.71429      6.428571      12.85714  21 65.7 1.668783 65.26077 143.9
##        BMI    Sex English CESDScore Education  Race
## 1 22.40325 Female English         5        19 White
## 2 22.40325 Female English         5        19 White
## 3 22.40325 Female English         5        19 White
## 4 23.43610 Female English         1        14 White
## 5 23.43610 Female English         1        14 White
## 6 23.43610 Female English         1        14 White
##   X  Sub_ID Appointment_Number ItemOrdr                   ItemID Response Score
## 1 1 MAE_001      Appointment_1        1      FLANKER_ARROW_PRAC1        1     1
## 2 2 MAE_001      Appointment_1        2      FLANKER_ARROW_PRAC2        2     1
## 3 3 MAE_001      Appointment_1        3      FLANKER_ARROW_PRAC3        1     1
## 4 4 MAE_001      Appointment_1        4      FLANKER_ARROW_PRAC4        2     1
## 5 5 MAE_001      Appointment_1        1 FLANKER_ARROW_CONGRUENT1        1     1
## 6 6 MAE_001      Appointment_1        2 FLANKER_ARROW_CONGRUENT2        2     1
##   ResponseTime         DateCreated
## 1     0.558145 2021-11-15 10:13:28
## 2     0.461735 2021-11-15 10:13:34
## 3     0.459106 2021-11-15 10:13:40
## 4     0.432569 2021-11-15 10:13:46
## 5     0.401191 2021-11-15 10:14:01
## 6     0.281966 2021-11-15 10:14:06

Data Cleaning

Table 1 - Demographic Data

-Jena Moody’s functions utilized here -Table copied and pasted and then manually formatted in Microsoft Word for final version

Characteristics of Study Participants
Female
(N=9)
Male
(N=9)
Overall
(N=18)

Sedentary,Walking,Moderate Intensity,Vigorous Intensity time estimates per day were collected as subjective estimates through the IPAQ-SF. Notes: BMI= body mass index; CES-D= Center for Epidemiological Studies Depression Scale.

Age (years)
Mean (SD) 21.1 (2.57) 22.0 (2.74) 21.6 (2.62)
Education (years)
Mean (SD) 15.0 (2.55) 15.6 (2.74) 15.3 (2.59)
CES-D
Mean (SD) 5.44 (3.84) 7.22 (3.87) 6.33 (3.85)
Height (M)
Mean (SD) 1.66 (0.0537) 1.71 (0.0732) 1.68 (0.0680)
Weight (Kg)
Mean (SD) 70.2 (10.7) 71.8 (11.7) 71.0 (10.9)
BMI (Kg/m^2)
Mean (SD) 25.6 (3.62) 24.8 (5.10) 25.2 (4.31)
Sedentary Time (hours/day)
Mean (SD) 7.50 (1.54) 7.89 (2.85) 7.69 (2.23)
Time Spent Walking (hours/day)
Mean (SD) 1.17 (1.18) 1.18 (1.87) 1.18 (1.52)
Time Spent at Moderate Intensity (hours/day)
Mean (SD) 0.288 (0.273) 0.858 (1.27) 0.573 (0.936)
Time Spent at Vigorous Intensity (hours/day)
Mean (SD) 0.332 (0.322) 0.787 (0.544) 0.560 (0.493)
Race
Asian 1 (11.1%) 4 (44.4%) 5 (27.8%)
Prefer_Not_Say 1 (11.1%) 0 (0%) 1 (5.6%)
White 7 (77.8%) 5 (55.6%) 12 (66.7%)

Table 2 - Exercise Manipulation Summary

-HR continuously collected and RPE collected every min (except for control condition where RPE collected at beginning and end)

-Mean HR/RPE computed during each session for each participant -Mean (SD) then computed across all participants

-Example: Mean of Sub 1 computed during their rest appt (70 BPM; 6 RPE) -Example: Mean and SD of ALL individual rest means computed (HR/RPE) computed

-Table data copied and pasted into Microsoft Word and manually formatted for final version

## [1] 11.2 18.2 18.3
## [1] 3.1
##           Condition Mean Mean RPE Mean Mean HR SD Mean HR
## 1           Control             6        83.25       11.5
## 2    Light Exercise          9.07       110.36       2.96
## 3 Vigorous Exercise         13.27       147.98       3.14
##   Mean Percentage of Time in Zone Mean Lower THR Bound Mean Upper THR Bound
## 1                  Not Applicable       Not Applicable       Not Applicable
## 2                           0.928               104.56               115.89
## 3                           0.906               142.48               153.83
##   SD Mean RPE Mean Mean %HRR SD Mean %HRR
## 1           0           13.1         5.49
## 2        0.69          34.61         2.36
## 3        0.84          64.37          2.5

Results - Exercise Manipulation

-I have code for One-Way ANOVAs for the main effect of condition on Avg HR/RPE -We chose not to incorporate these results into the paper -Missing data (HR: 3.1, RPE: 11.2, 18.2, 18.3) -Complicated scenario (Participant 16 completed light condition twice) -Assumptions of ANOVA violated -(RPE data severely violates normality assumptions) -(HR data more variable for exercise versus rest)

Results - Continuous MST

-Followed this approach: 1.) Completed ANOVA and Post-Hoc BEFORE verifying assumptions 2.) Verified assumptions and removed outliers (>3 sd from mean) 3.) Re-did ANOVA and Post-Hoc With Outliers removed

-Retained original analysis if outliers didn’t impact results -Primary Outcome Measures: LDI (Lure Bins 1-3)

1.) ANOVA/Post-Hoc

## ANOVA Table (type III tests)
## 
##                      Effect DFn DFd      F                p p<.05      ges
## 1                 Condition   2  32  0.022 0.97800000000000       0.000212
## 2           Lure_Similarity   2  32 71.661 0.00000000000152     * 0.327000
## 3 Condition:Lure_Similarity   4  64  0.316 0.86600000000000       0.005000
## # A tibble: 9 × 11
##   Condition .y.        group1 group2    n1    n2 statistic    df       p   p.adj
## * <chr>     <chr>      <chr>  <chr>  <int> <int>     <dbl> <dbl>   <dbl>   <dbl>
## 1 Control   Lure_Disc… High   Low       17    17     -6.10    16 1.52e-5 4.56e-5
## 2 Control   Lure_Disc… High   Medium    17    17     -4.30    16 5.48e-4 2   e-3
## 3 Control   Lure_Disc… Low    Medium    17    17      1.70    16 1.08e-1 3.24e-1
## 4 Light     Lure_Disc… High   Low       17    17     -6.95    16 3.26e-6 9.78e-6
## 5 Light     Lure_Disc… High   Medium    17    17     -5.38    16 6.17e-5 1.85e-4
## 6 Light     Lure_Disc… Low    Medium    17    17      2.30    16 3.5 e-2 1.05e-1
## 7 Vigorous  Lure_Disc… High   Low       17    17     -6.17    16 1.35e-5 4.05e-5
## 8 Vigorous  Lure_Disc… High   Medium    17    17     -3.18    16 6   e-3 1.7 e-2
## 9 Vigorous  Lure_Disc… Low    Medium    17    17      3.00    16 8   e-3 2.5 e-2
## # ℹ 1 more variable: p.adj.signif <chr>
## ANOVA Table (type III tests)
## 
##   Effect DFn DFd     F     p p<.05   ges
## 1   Cond   2  32 0.149 0.862       0.003

2.) Assumption Verification/Outlier Removal - LDI

LDI: -Normality violated for (Control and Vigorous Low Similarity) -Equal Variance Test not violated -Outlier detected (# 7) and removed

RM: -Normality severely violated -Equal Variance Test not violated -Chose not to perform outlier removal etc. due to severe violation of ANOVA assumptions -Additionally, this wasn’t a primary measure of interest

##   Condition Lure_Similarity                  variable statistic           p
## 1   Control            High Lure_Discrimination_Index 0.9665915 0.756427913
## 2   Control             Low Lure_Discrimination_Index 0.8196430 0.003820651
## 3   Control          Medium Lure_Discrimination_Index 0.9385815 0.301749272
## 4     Light            High Lure_Discrimination_Index 0.9608603 0.647706289
## 5     Light             Low Lure_Discrimination_Index 0.9293440 0.212209676
## 6     Light          Medium Lure_Discrimination_Index 0.9506892 0.467511858
## 7  Vigorous            High Lure_Discrimination_Index 0.9822780 0.974952592
## 8  Vigorous             Low Lure_Discrimination_Index 0.7899678 0.001482829
## 9  Vigorous          Medium Lure_Discrimination_Index 0.9408985 0.328995138
## Levene's Test for Homogeneity of Variance (center = median)
##        Df F value Pr(>F)
## group   8  0.9906 0.4459
##       144
## # A tibble: 153 × 5
##    Condition Sub_ID Lure_Similarity Lure_Discrimination_Index z_score[,1]
##    <chr>      <int> <chr>                               <dbl>       <dbl>
##  1 Control        1 Low                                 0.946      0.661 
##  2 Light          1 Low                                 0.926      0.874 
##  3 Vigorous       1 Low                                 0.926      0.572 
##  4 Vigorous       2 Low                                 0.812      0.0328
##  5 Control        2 Low                                 0.662     -0.478 
##  6 Light          2 Low                                 0.469     -1.75  
##  7 Vigorous       4 Low                                 0.644     -0.765 
##  8 Control        4 Low                                 0.693     -0.353 
##  9 Light          4 Low                                 0.780      0.0339
## 10 Light          5 Low                                 0.667     -0.612 
## # ℹ 143 more rows
##       Cond           variable statistic           p
## 1  Control Recognition.Memory 0.9306179 0.222881793
## 2    Light Recognition.Memory 0.8237508 0.004376191
## 3 Vigorous Recognition.Memory 0.9068220 0.088422079
## Levene's Test for Homogeneity of Variance (center = median)
##       Df F value Pr(>F)
## group  2  0.0293 0.9712
##       48

3.) ANOVA/Post-Hoc

LDI: -Results unchanged by outlier removal -Initial ANOVA results utilized in manuscript

## ANOVA Table (type III tests)
## 
##                      Effect DFn DFd      F                 p p<.05   ges
## 1                 Condition   2  30  0.096 0.909000000000000       0.001
## 2           Lure_Similarity   2  30 85.863 0.000000000000385     * 0.377
## 3 Condition:Lure_Similarity   4  60  0.405 0.804000000000000       0.007
## # A tibble: 9 × 11
##   Condition .y.        group1 group2    n1    n2 statistic    df       p   p.adj
## * <chr>     <chr>      <chr>  <chr>  <int> <int>     <dbl> <dbl>   <dbl>   <dbl>
## 1 Control   Lure_Disc… High   Low       16    16     -5.76    15 3.73e-5 1.12e-4
## 2 Control   Lure_Disc… High   Medium    16    16     -3.95    15 1   e-3 4   e-3
## 3 Control   Lure_Disc… Low    Medium    16    16      1.82    15 8.9 e-2 2.66e-1
## 4 Light     Lure_Disc… High   Low       16    16     -6.86    15 5.42e-6 1.63e-5
## 5 Light     Lure_Disc… High   Medium    16    16     -5.38    15 7.6 e-5 2.28e-4
## 6 Light     Lure_Disc… Low    Medium    16    16      2.15    15 4.8 e-2 1.46e-1
## 7 Vigorous  Lure_Disc… High   Low       16    16     -9.95    15 5.33e-8 1.6 e-7
## 8 Vigorous  Lure_Disc… High   Medium    16    16     -3.50    15 3   e-3 1   e-2
## 9 Vigorous  Lure_Disc… Low    Medium    16    16      3.61    15 3   e-3 8   e-3
## # ℹ 1 more variable: p.adj.signif <chr>

4.) Plotting

*LDI versus Condition (Facet wrapped by Lure Similarity)

-outliers greater than 3 sd included in these plots (results not impacted by inclusion) -unadjusted p-values utilized

*LDI versus Lure Similarity (Facet wrapped by Condition)

-outliers greater than 3 sd included in these plots (results not impacted by inclusion) -unadjusted p-values utilized

### *Proportion of Responses

*Saving Plots

5.) Correlations

-Goal of this analysis was to explore correlation between exercise induced changes in LDI -Computed change scores (Vig - Rest, Vig - Light, Light - Rest) and plotted against baseline level of PA

Variables: Overall LDI (across lure bin difficulty) for rest, light, and vigorous conditions, and total IPAQ METs

*Data Cleaning

*Mixed Models (NOT REVIEWED/IN PAPER)

This was exploratory and not reviewed or included in the paper.

## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Lure_Discrimination_Index ~ Cond * Lure_Similarity + (1 | Sub_ID)
##    Data: B_M_Final
## 
## REML criterion at convergence: -82.3
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -2.8923 -0.4710  0.0364  0.6785  2.3760 
## 
## Random effects:
##  Groups   Name        Variance Std.Dev.
##  Sub_ID   (Intercept) 0.01717  0.1310  
##  Residual             0.02198  0.1482  
## Number of obs: 153, groups:  Sub_ID, 17
## 
## Fixed effects:
##                                      Estimate Std. Error         df t value
## (Intercept)                          0.455383   0.047987  56.721150   9.490
## CondLight                            0.007978   0.050849 128.000000   0.157
## CondVigorous                         0.026465   0.050849 128.000000   0.520
## Lure_SimilarityLow                   0.326050   0.050849 128.000000   6.412
## Lure_SimilarityMedium                0.243035   0.050849 128.000000   4.780
## CondLight:Lure_SimilarityLow        -0.015756   0.071912 128.000000  -0.219
## CondVigorous:Lure_SimilarityLow     -0.002326   0.071912 128.000000  -0.032
## CondLight:Lure_SimilarityMedium     -0.006844   0.071912 128.000000  -0.095
## CondVigorous:Lure_SimilarityMedium  -0.058666   0.071912 128.000000  -0.816
##                                            Pr(>|t|)    
## (Intercept)                        0.00000000000026 ***
## CondLight                                     0.876    
## CondVigorous                                  0.604    
## Lure_SimilarityLow                 0.00000000252654 ***
## Lure_SimilarityMedium              0.00000474225002 ***
## CondLight:Lure_SimilarityLow                  0.827    
## CondVigorous:Lure_SimilarityLow               0.974    
## CondLight:Lure_SimilarityMedium               0.924    
## CondVigorous:Lure_SimilarityMedium            0.416    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Correlation of Fixed Effects:
##             (Intr) CndLgh CndVgr Lr_SmL Lr_SmM CL:L_SL CV:L_SL CL:L_SM
## CondLight   -0.530                                                    
## CondVigoros -0.530  0.500                                             
## Lr_SmlrtyLw -0.530  0.500  0.500                                      
## Lr_SmlrtyMd -0.530  0.500  0.500  0.500                               
## CndLgh:L_SL  0.375 -0.707 -0.354 -0.707 -0.354                        
## CndVgr:L_SL  0.375 -0.354 -0.707 -0.707 -0.354  0.500                 
## CndLgh:L_SM  0.375 -0.707 -0.354 -0.354 -0.707  0.500   0.250         
## CndVgr:L_SM  0.375 -0.354 -0.707 -0.354 -0.707  0.250   0.500   0.500
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Lure_Discrimination_Index ~ Cond * Lure_Similarity * TotPAMET +  
##     (1 | Sub_ID)
##    Data: B_M_Final
## 
## REML criterion at convergence: 83.1
## 
## Scaled residuals: 
##      Min       1Q   Median       3Q      Max 
## -2.89321 -0.49205  0.03367  0.70699  1.98863 
## 
## Random effects:
##  Groups   Name        Variance Std.Dev.
##  Sub_ID   (Intercept) 0.01855  0.1362  
##  Residual             0.02120  0.1456  
## Number of obs: 153, groups:  Sub_ID, 17
## 
## Fixed effects:
##                                                 Estimate   Std. Error
## (Intercept)                                   0.59700930   0.09780794
## CondLight                                    -0.14376194   0.10102029
## CondVigorous                                 -0.22544185   0.10102029
## Lure_SimilarityLow                            0.27340341   0.10102029
## Lure_SimilarityMedium                         0.08580353   0.10102029
## TotPAMET                                     -0.00004098   0.00002460
## CondLight:Lure_SimilarityLow                  0.02071101   0.14286426
## CondVigorous:Lure_SimilarityLow               0.18797842   0.14286426
## CondLight:Lure_SimilarityMedium               0.08358703   0.14286426
## CondVigorous:Lure_SimilarityMedium            0.24680769   0.14286426
## CondLight:TotPAMET                            0.00004391   0.00002541
## CondVigorous:TotPAMET                         0.00007289   0.00002541
## Lure_SimilarityLow:TotPAMET                   0.00001523   0.00002541
## Lure_SimilarityMedium:TotPAMET                0.00004550   0.00002541
## CondLight:Lure_SimilarityLow:TotPAMET        -0.00001055   0.00003594
## CondVigorous:Lure_SimilarityLow:TotPAMET     -0.00005507   0.00003594
## CondLight:Lure_SimilarityMedium:TotPAMET     -0.00002617   0.00003594
## CondVigorous:Lure_SimilarityMedium:TotPAMET  -0.00008840   0.00003594
##                                                       df t value    Pr(>|t|)
## (Intercept)                                  49.23677204   6.104 0.000000159
## CondLight                                   120.00000038  -1.423     0.15730
## CondVigorous                                120.00000035  -2.232     0.02749
## Lure_SimilarityLow                          120.00000039   2.706     0.00779
## Lure_SimilarityMedium                       120.00000034   0.849     0.39737
## TotPAMET                                     49.23677192  -1.666     0.10210
## CondLight:Lure_SimilarityLow                120.00000044   0.145     0.88498
## CondVigorous:Lure_SimilarityLow             120.00000041   1.316     0.19075
## CondLight:Lure_SimilarityMedium             120.00000036   0.585     0.55959
## CondVigorous:Lure_SimilarityMedium          120.00000037   1.728     0.08664
## CondLight:TotPAMET                          120.00000052   1.728     0.08656
## CondVigorous:TotPAMET                       120.00000047   2.869     0.00487
## Lure_SimilarityLow:TotPAMET                 120.00000053   0.600     0.54994
## Lure_SimilarityMedium:TotPAMET              120.00000047   1.791     0.07588
## CondLight:Lure_SimilarityLow:TotPAMET       120.00000054  -0.294     0.76953
## CondVigorous:Lure_SimilarityLow:TotPAMET    120.00000050  -1.532     0.12805
## CondLight:Lure_SimilarityMedium:TotPAMET    120.00000046  -0.728     0.46791
## CondVigorous:Lure_SimilarityMedium:TotPAMET 120.00000045  -2.460     0.01532
##                                                
## (Intercept)                                 ***
## CondLight                                      
## CondVigorous                                *  
## Lure_SimilarityLow                          ** 
## Lure_SimilarityMedium                          
## TotPAMET                                       
## CondLight:Lure_SimilarityLow                   
## CondVigorous:Lure_SimilarityLow                
## CondLight:Lure_SimilarityMedium                
## CondVigorous:Lure_SimilarityMedium          .  
## CondLight:TotPAMET                          .  
## CondVigorous:TotPAMET                       ** 
## Lure_SimilarityLow:TotPAMET                    
## Lure_SimilarityMedium:TotPAMET              .  
## CondLight:Lure_SimilarityLow:TotPAMET          
## CondVigorous:Lure_SimilarityLow:TotPAMET       
## CondLight:Lure_SimilarityMedium:TotPAMET       
## CondVigorous:Lure_SimilarityMedium:TotPAMET *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## fit warnings:
## Some predictor variables are on very different scales: consider rescaling
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Lure_Discrimination_Index ~ Age + Sex + BMI + Race + CESDScore +  
##     Education + Recognition.Memory + Cond * Lure_Similarity +      (1 | Sub_ID)
##    Data: B_M_Final
## 
## REML criterion at convergence: -60.2
## 
## Scaled residuals: 
##      Min       1Q   Median       3Q      Max 
## -2.76847 -0.52998  0.03857  0.74708  2.41480 
## 
## Random effects:
##  Groups   Name        Variance Std.Dev.
##  Sub_ID   (Intercept) 0.007986 0.08936 
##  Residual             0.022126 0.14875 
## Number of obs: 153, groups:  Sub_ID, 17
## 
## Fixed effects:
##                                      Estimate Std. Error         df t value
## (Intercept)                          1.053850   0.444165   9.903669   2.373
## Age                                 -0.129485   0.050658   8.400202  -2.556
## SexMale                             -0.021373   0.062536   8.407600  -0.342
## BMI                                 -0.005289   0.006620   8.397530  -0.799
## RacePrefer_Not_Say                   0.020500   0.131461   8.294586   0.156
## RaceWhite                            0.002478   0.063235   8.336075   0.039
## CESDScore                           -0.013482   0.008606   8.403718  -1.567
## Education                            0.157114   0.051330   8.394262   3.061
## Recognition.Memory                   0.025959   0.213849  76.017264   0.121
## CondLight                            0.007703   0.051070 126.923860   0.151
## CondVigorous                         0.026238   0.051054 126.877764   0.514
## Lure_SimilarityLow                   0.326050   0.051020 126.778945   6.391
## Lure_SimilarityMedium                0.243035   0.051020 126.778945   4.764
## CondLight:Lure_SimilarityLow        -0.015756   0.072153 126.778945  -0.218
## CondVigorous:Lure_SimilarityLow     -0.002326   0.072153 126.778945  -0.032
## CondLight:Lure_SimilarityMedium     -0.006844   0.072153 126.778945  -0.095
## CondVigorous:Lure_SimilarityMedium  -0.058666   0.072153 126.778945  -0.813
##                                         Pr(>|t|)    
## (Intercept)                               0.0393 *  
## Age                                       0.0326 *  
## SexMale                                   0.7409    
## BMI                                       0.4464    
## RacePrefer_Not_Say                        0.8798    
## RaceWhite                                 0.9697    
## CESDScore                                 0.1540    
## Education                                 0.0147 *  
## Recognition.Memory                        0.9037    
## CondLight                                 0.8803    
## CondVigorous                              0.6082    
## Lure_SimilarityLow                 0.00000000287 ***
## Lure_SimilarityMedium              0.00000511572 ***
## CondLight:Lure_SimilarityLow              0.8275    
## CondVigorous:Lure_SimilarityLow           0.9743    
## CondLight:Lure_SimilarityMedium           0.9246    
## CondVigorous:Lure_SimilarityMedium        0.4177    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Lure_Discrimination_Index ~ Age + Sex + BMI + Race + CESDScore +  
##     Education + Recognition.Memory + Cond * Lure_Similarity *  
##     TotPAMET + (1 | Sub_ID)
##    Data: B_M_Final
## 
## REML criterion at convergence: 104.5
## 
## Scaled residuals: 
##      Min       1Q   Median       3Q      Max 
## -2.76100 -0.48986 -0.00035  0.61738  2.04367 
## 
## Random effects:
##  Groups   Name        Variance Std.Dev.
##  Sub_ID   (Intercept) 0.008516 0.09228 
##  Residual             0.021362 0.14616 
## Number of obs: 153, groups:  Sub_ID, 17
## 
## Fixed effects:
##                                                 Estimate   Std. Error
## (Intercept)                                   1.28754351   0.49107427
## Age                                          -0.14740843   0.05692462
## SexMale                                      -0.00357848   0.06792016
## BMI                                          -0.00581527   0.00678042
## RacePrefer_Not_Say                            0.02581871   0.13458752
## RaceWhite                                     0.02523261   0.07150212
## CESDScore                                    -0.01777922   0.01085285
## Education                                     0.17291506   0.05637730
## Recognition.Memory                            0.04945819   0.21853287
## CondLight                                    -0.14610172   0.10192864
## CondVigorous                                 -0.22549902   0.10140330
## Lure_SimilarityLow                            0.27340341   0.10140298
## Lure_SimilarityMedium                         0.08580353   0.10140298
## TotPAMET                                     -0.00002662   0.00002481
## CondLight:Lure_SimilarityLow                  0.02071101   0.14340548
## CondVigorous:Lure_SimilarityLow               0.18797842   0.14340548
## CondLight:Lure_SimilarityMedium               0.08358703   0.14340548
## CondVigorous:Lure_SimilarityMedium            0.24680769   0.14340548
## CondLight:TotPAMET                            0.00004443   0.00002561
## CondVigorous:TotPAMET                         0.00007279   0.00002551
## Lure_SimilarityLow:TotPAMET                   0.00001523   0.00002551
## Lure_SimilarityMedium:TotPAMET                0.00004550   0.00002551
## CondLight:Lure_SimilarityLow:TotPAMET        -0.00001055   0.00003607
## CondVigorous:Lure_SimilarityLow:TotPAMET     -0.00005507   0.00003607
## CondLight:Lure_SimilarityMedium:TotPAMET     -0.00002617   0.00003607
## CondVigorous:Lure_SimilarityMedium:TotPAMET  -0.00008840   0.00003607
##                                                       df t value Pr(>|t|)   
## (Intercept)                                   9.50662948   2.622  0.02654 * 
## Age                                           7.56387117  -2.590  0.03367 * 
## SexMale                                       7.58226205  -0.053  0.95934   
## BMI                                           7.64865252  -0.858  0.41714   
## RacePrefer_Not_Say                            7.59465530   0.192  0.85290   
## RaceWhite                                     7.54653755   0.353  0.73382   
## CESDScore                                     7.86619628  -1.638  0.14065   
## Education                                     7.57090577   3.067  0.01648 * 
## Recognition.Memory                           74.91730511   0.226  0.82157   
## CondLight                                   119.69135611  -1.433  0.15436   
## CondVigorous                                119.05454946  -2.224  0.02805 * 
## Lure_SimilarityLow                          119.05415864   2.696  0.00803 **
## Lure_SimilarityMedium                       119.05415864   0.846  0.39916   
## TotPAMET                                     26.62761730  -1.073  0.29280   
## CondLight:Lure_SimilarityLow                119.05415860   0.144  0.88541   
## CondVigorous:Lure_SimilarityLow             119.05415858   1.311  0.19244   
## CondLight:Lure_SimilarityMedium             119.05415860   0.583  0.56108   
## CondVigorous:Lure_SimilarityMedium          119.05415857   1.721  0.08784 . 
## CondLight:TotPAMET                          119.56476650   1.735  0.08533 . 
## CondVigorous:TotPAMET                       119.07642872   2.853  0.00511 **
## Lure_SimilarityLow:TotPAMET                 119.05415854   0.597  0.55145   
## Lure_SimilarityMedium:TotPAMET              119.05415853   1.784  0.07700 . 
## CondLight:Lure_SimilarityLow:TotPAMET       119.05415853  -0.293  0.77038   
## CondVigorous:Lure_SimilarityLow:TotPAMET    119.05415852  -1.527  0.12950   
## CondLight:Lure_SimilarityMedium:TotPAMET    119.05415853  -0.725  0.46960   
## CondVigorous:Lure_SimilarityMedium:TotPAMET 119.05415851  -2.451  0.01572 * 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## fit warnings:
## Some predictor variables are on very different scales: consider rescaling
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Lure_Discrimination_Index ~ Age + Sex + BMI + Race + CESDScore +  
##     Education + Recognition.Memory + Cond * Lure_Similarity *  
##     TotPAMET_zcat + (1 | Sub_ID)
##    Data: B_M_Final
## 
## REML criterion at convergence: -33.3
## 
## Scaled residuals: 
##      Min       1Q   Median       3Q      Max 
## -2.80988 -0.52129  0.04966  0.59092  2.26148 
## 
## Random effects:
##  Groups   Name        Variance Std.Dev.
##  Sub_ID   (Intercept) 0.005157 0.07181 
##  Residual             0.022616 0.15039 
## Number of obs: 153, groups:  Sub_ID, 17
## 
## Fixed effects:
##                                                                    Estimate
## (Intercept)                                                        1.111593
## Age                                                               -0.178911
## SexMale                                                           -0.041418
## BMI                                                               -0.005683
## RacePrefer_Not_Say                                                -0.007113
## RaceWhite                                                          0.029275
## CESDScore                                                         -0.012979
## Education                                                          0.210929
## Recognition.Memory                                                 0.191490
## CondLight                                                         -0.180071
## CondVigorous                                                      -0.135857
## Lure_SimilarityLow                                                 0.333333
## Lure_SimilarityMedium                                              0.136905
## TotPAMET_zcat> 1                                                  -0.042573
## TotPAMET_zcatBetween -1 and 1                                      0.064317
## CondLight:Lure_SimilarityLow                                       0.060606
## CondVigorous:Lure_SimilarityLow                                    0.049784
## CondLight:Lure_SimilarityMedium                                    0.120671
## CondVigorous:Lure_SimilarityMedium                                -0.015693
## CondLight:TotPAMET_zcat> 1                                         0.288660
## CondVigorous:TotPAMET_zcat> 1                                      0.324562
## CondLight:TotPAMET_zcatBetween -1 and 1                            0.191362
## CondVigorous:TotPAMET_zcatBetween -1 and 1                         0.146443
## Lure_SimilarityLow:TotPAMET_zcat> 1                                0.018182
## Lure_SimilarityMedium:TotPAMET_zcat> 1                             0.159055
## Lure_SimilarityLow:TotPAMET_zcatBetween -1 and 1                  -0.014863
## Lure_SimilarityMedium:TotPAMET_zcatBetween -1 and 1                0.110588
## CondLight:Lure_SimilarityLow:TotPAMET_zcat> 1                     -0.001347
## CondVigorous:Lure_SimilarityLow:TotPAMET_zcat> 1                  -0.177393
## CondLight:Lure_SimilarityMedium:TotPAMET_zcat> 1                  -0.093158
## CondVigorous:Lure_SimilarityMedium:TotPAMET_zcat> 1               -0.302393
## CondLight:Lure_SimilarityLow:TotPAMET_zcatBetween -1 and 1        -0.107843
## CondVigorous:Lure_SimilarityLow:TotPAMET_zcatBetween -1 and 1     -0.029473
## CondLight:Lure_SimilarityMedium:TotPAMET_zcatBetween -1 and 1     -0.157356
## CondVigorous:Lure_SimilarityMedium:TotPAMET_zcatBetween -1 and 1   0.014719
##                                                                  Std. Error
## (Intercept)                                                        0.429549
## Age                                                                0.049452
## SexMale                                                            0.059455
## BMI                                                                0.005855
## RacePrefer_Not_Say                                                 0.113743
## RaceWhite                                                          0.056328
## CESDScore                                                          0.008614
## Education                                                          0.050910
## Recognition.Memory                                                 0.227269
## CondLight                                                          0.151527
## CondVigorous                                                       0.150488
## Lure_SimilarityLow                                                 0.150385
## Lure_SimilarityMedium                                              0.150385
## TotPAMET_zcat> 1                                                   0.163634
## TotPAMET_zcatBetween -1 and 1                                      0.139601
## CondLight:Lure_SimilarityLow                                       0.212677
## CondVigorous:Lure_SimilarityLow                                    0.212677
## CondLight:Lure_SimilarityMedium                                    0.212677
## CondVigorous:Lure_SimilarityMedium                                 0.212677
## CondLight:TotPAMET_zcat> 1                                         0.195635
## CondVigorous:TotPAMET_zcat> 1                                      0.194308
## CondLight:TotPAMET_zcatBetween -1 and 1                            0.163308
## CondVigorous:TotPAMET_zcatBetween -1 and 1                         0.162464
## Lure_SimilarityLow:TotPAMET_zcat> 1                                0.194146
## Lure_SimilarityMedium:TotPAMET_zcat> 1                             0.194146
## Lure_SimilarityLow:TotPAMET_zcatBetween -1 and 1                   0.162434
## Lure_SimilarityMedium:TotPAMET_zcatBetween -1 and 1                0.162434
## CondLight:Lure_SimilarityLow:TotPAMET_zcat> 1                      0.274564
## CondVigorous:Lure_SimilarityLow:TotPAMET_zcat> 1                   0.274564
## CondLight:Lure_SimilarityMedium:TotPAMET_zcat> 1                   0.274564
## CondVigorous:Lure_SimilarityMedium:TotPAMET_zcat> 1                0.274564
## CondLight:Lure_SimilarityLow:TotPAMET_zcatBetween -1 and 1         0.229717
## CondVigorous:Lure_SimilarityLow:TotPAMET_zcatBetween -1 and 1      0.229717
## CondLight:Lure_SimilarityMedium:TotPAMET_zcatBetween -1 and 1      0.229717
## CondVigorous:Lure_SimilarityMedium:TotPAMET_zcatBetween -1 and 1   0.229717
##                                                                          df
## (Intercept)                                                        8.802617
## Age                                                                5.775916
## SexMale                                                            5.678353
## BMI                                                                5.657853
## RacePrefer_Not_Say                                                 5.747884
## RaceWhite                                                          5.672051
## CESDScore                                                          6.438600
## Education                                                          5.794539
## Recognition.Memory                                                64.033989
## CondLight                                                        110.923092
## CondVigorous                                                     110.048060
## Lure_SimilarityLow                                               109.958364
## Lure_SimilarityMedium                                            109.958364
## TotPAMET_zcat> 1                                                  38.920316
## TotPAMET_zcatBetween -1 and 1                                     33.111942
## CondLight:Lure_SimilarityLow                                     109.958364
## CondVigorous:Lure_SimilarityLow                                  109.958364
## CondLight:Lure_SimilarityMedium                                  109.958364
## CondVigorous:Lure_SimilarityMedium                               109.958364
## CondLight:TotPAMET_zcat> 1                                       110.932444
## CondVigorous:TotPAMET_zcat> 1                                    110.067688
## CondLight:TotPAMET_zcatBetween -1 and 1                          110.648982
## CondVigorous:TotPAMET_zcatBetween -1 and 1                       109.982006
## Lure_SimilarityLow:TotPAMET_zcat> 1                              109.958364
## Lure_SimilarityMedium:TotPAMET_zcat> 1                           109.958364
## Lure_SimilarityLow:TotPAMET_zcatBetween -1 and 1                 109.958364
## Lure_SimilarityMedium:TotPAMET_zcatBetween -1 and 1              109.958364
## CondLight:Lure_SimilarityLow:TotPAMET_zcat> 1                    109.958364
## CondVigorous:Lure_SimilarityLow:TotPAMET_zcat> 1                 109.958364
## CondLight:Lure_SimilarityMedium:TotPAMET_zcat> 1                 109.958364
## CondVigorous:Lure_SimilarityMedium:TotPAMET_zcat> 1              109.958364
## CondLight:Lure_SimilarityLow:TotPAMET_zcatBetween -1 and 1       109.958364
## CondVigorous:Lure_SimilarityLow:TotPAMET_zcatBetween -1 and 1    109.958364
## CondLight:Lure_SimilarityMedium:TotPAMET_zcatBetween -1 and 1    109.958364
## CondVigorous:Lure_SimilarityMedium:TotPAMET_zcatBetween -1 and 1 109.958364
##                                                                  t value
## (Intercept)                                                        2.588
## Age                                                               -3.618
## SexMale                                                           -0.697
## BMI                                                               -0.971
## RacePrefer_Not_Say                                                -0.063
## RaceWhite                                                          0.520
## CESDScore                                                         -1.507
## Education                                                          4.143
## Recognition.Memory                                                 0.843
## CondLight                                                         -1.188
## CondVigorous                                                      -0.903
## Lure_SimilarityLow                                                 2.217
## Lure_SimilarityMedium                                              0.910
## TotPAMET_zcat> 1                                                  -0.260
## TotPAMET_zcatBetween -1 and 1                                      0.461
## CondLight:Lure_SimilarityLow                                       0.285
## CondVigorous:Lure_SimilarityLow                                    0.234
## CondLight:Lure_SimilarityMedium                                    0.567
## CondVigorous:Lure_SimilarityMedium                                -0.074
## CondLight:TotPAMET_zcat> 1                                         1.476
## CondVigorous:TotPAMET_zcat> 1                                      1.670
## CondLight:TotPAMET_zcatBetween -1 and 1                            1.172
## CondVigorous:TotPAMET_zcatBetween -1 and 1                         0.901
## Lure_SimilarityLow:TotPAMET_zcat> 1                                0.094
## Lure_SimilarityMedium:TotPAMET_zcat> 1                             0.819
## Lure_SimilarityLow:TotPAMET_zcatBetween -1 and 1                  -0.092
## Lure_SimilarityMedium:TotPAMET_zcatBetween -1 and 1                0.681
## CondLight:Lure_SimilarityLow:TotPAMET_zcat> 1                     -0.005
## CondVigorous:Lure_SimilarityLow:TotPAMET_zcat> 1                  -0.646
## CondLight:Lure_SimilarityMedium:TotPAMET_zcat> 1                  -0.339
## CondVigorous:Lure_SimilarityMedium:TotPAMET_zcat> 1               -1.101
## CondLight:Lure_SimilarityLow:TotPAMET_zcatBetween -1 and 1        -0.469
## CondVigorous:Lure_SimilarityLow:TotPAMET_zcatBetween -1 and 1     -0.128
## CondLight:Lure_SimilarityMedium:TotPAMET_zcatBetween -1 and 1     -0.685
## CondVigorous:Lure_SimilarityMedium:TotPAMET_zcatBetween -1 and 1   0.064
##                                                                  Pr(>|t|)   
## (Intercept)                                                       0.02983 * 
## Age                                                               0.01188 * 
## SexMale                                                           0.51352   
## BMI                                                               0.37134   
## RacePrefer_Not_Say                                                0.95226   
## RaceWhite                                                         0.62291   
## CESDScore                                                         0.17925   
## Education                                                         0.00653 **
## Recognition.Memory                                                0.40261   
## CondLight                                                         0.23722   
## CondVigorous                                                      0.36862   
## Lure_SimilarityLow                                                0.02871 * 
## Lure_SimilarityMedium                                             0.36462   
## TotPAMET_zcat> 1                                                  0.79610   
## TotPAMET_zcatBetween -1 and 1                                     0.64801   
## CondLight:Lure_SimilarityLow                                      0.77620   
## CondVigorous:Lure_SimilarityLow                                   0.81536   
## CondLight:Lure_SimilarityMedium                                   0.57160   
## CondVigorous:Lure_SimilarityMedium                                0.94131   
## CondLight:TotPAMET_zcat> 1                                        0.14291   
## CondVigorous:TotPAMET_zcat> 1                                     0.09769 . 
## CondLight:TotPAMET_zcatBetween -1 and 1                           0.24380   
## CondVigorous:TotPAMET_zcatBetween -1 and 1                        0.36935   
## Lure_SimilarityLow:TotPAMET_zcat> 1                               0.92556   
## Lure_SimilarityMedium:TotPAMET_zcat> 1                            0.41441   
## Lure_SimilarityLow:TotPAMET_zcatBetween -1 and 1                  0.92726   
## Lure_SimilarityMedium:TotPAMET_zcatBetween -1 and 1               0.49742   
## CondLight:Lure_SimilarityLow:TotPAMET_zcat> 1                     0.99610   
## CondVigorous:Lure_SimilarityLow:TotPAMET_zcat> 1                  0.51957   
## CondLight:Lure_SimilarityMedium:TotPAMET_zcat> 1                  0.73504   
## CondVigorous:Lure_SimilarityMedium:TotPAMET_zcat> 1               0.27315   
## CondLight:Lure_SimilarityLow:TotPAMET_zcatBetween -1 and 1        0.63967   
## CondVigorous:Lure_SimilarityLow:TotPAMET_zcatBetween -1 and 1     0.89814   
## CondLight:Lure_SimilarityMedium:TotPAMET_zcatBetween -1 and 1     0.49478   
## CondVigorous:Lure_SimilarityMedium:TotPAMET_zcatBetween -1 and 1  0.94903   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

*Run correlation for light - rest vs. Total METS

## 
##  Pearson's product-moment correlation
## 
## data:  B_M_Wide_JS$LDI_Light_Rest and B_M_Wide_JS$TotPAMET
## t = 2.1409, df = 15, p-value = 0.04912
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  0.004086662 0.782478618
## sample estimates:
##       cor 
## 0.4837812

*Plot

*Run correlation for vigorous - rest vs. Total METS

## 
##  Pearson's product-moment correlation
## 
## data:  B_M_Wide_JS$LDI_Vig_Rest and B_M_Wide_JS$TotPAMET
## t = 1.9334, df = 15, p-value = 0.07228
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  -0.04328711  0.76340692
## sample estimates:
##       cor 
## 0.4466505

*Plot

### *Saving Plots

Results - gradCPT

1.) ANOVA/Post-Hoc

-all participants expect #10 kept -Participant 16 completed 2 light appointments due to MST software malfunction. -First light appointment included below since gradCPT data was collected with no issues.

*dprime

## ANOVA Table (type III tests)
## 
##   Effect DFn DFd    F     p p<.05   ges
## 1   Cond   2  34 4.58 0.017     * 0.074
## # A tibble: 3 × 10
##   .y.    group1  group2      n1    n2 statistic    df     p p.adj p.adj.signif
## * <chr>  <chr>   <chr>    <int> <int>     <dbl> <dbl> <dbl> <dbl> <chr>       
## 1 dprime Control Light       18    18    -2.56     17 0.02  0.061 ns          
## 2 dprime Control Vigorous    18    18    -2.08     17 0.053 0.159 ns          
## 3 dprime Light   Vigorous    18    18     0.965    17 0.348 1     ns

*Criterion

## ANOVA Table (type III tests)
## 
##   Effect DFn DFd   F     p p<.05   ges
## 1   Cond   2  34 3.1 0.058       0.059
## # A tibble: 3 × 10
##   .y.       group1  group2     n1    n2 statistic    df     p p.adj p.adj.signif
## * <chr>     <chr>   <chr>   <int> <int>     <dbl> <dbl> <dbl> <dbl> <chr>       
## 1 criterion Control Light      18    18     2.58     17 0.019 0.058 ns          
## 2 criterion Control Vigoro…    18    18     1.40     17 0.178 0.534 ns          
## 3 criterion Light   Vigoro…    18    18    -0.931    17 0.365 1     ns

*Commission Rate

## ANOVA Table (type III tests)
## 
##   Effect DFn DFd     F     p p<.05   ges
## 1   Cond   2  34 7.277 0.002     * 0.099
## # A tibble: 3 × 10
##   .y.         group1 group2    n1    n2 statistic    df     p p.adj p.adj.signif
## * <chr>       <chr>  <chr>  <int> <int>     <dbl> <dbl> <dbl> <dbl> <chr>       
## 1 commission… Contr… Light     18    18      3.15    17 0.006 0.017 *           
## 2 commission… Contr… Vigor…    18    18      2.52    17 0.022 0.066 ns          
## 3 commission… Light  Vigor…    18    18     -1.33    17 0.2   0.6   ns

*Omission Rate

## ANOVA Table (type III tests)
## 
##   Effect  DFn   DFd     F     p p<.05   ges
## 1   Cond 1.16 19.68 0.689 0.437       0.023
## # A tibble: 3 × 10
##   .y.         group1 group2    n1    n2 statistic    df     p p.adj p.adj.signif
## * <chr>       <chr>  <chr>  <int> <int>     <dbl> <dbl> <dbl> <dbl> <chr>       
## 1 omission_r… Contr… Light     18    18  8.85e- 1    17 0.388     1 ns          
## 2 omission_r… Contr… Vigor…    18    18  8.23e- 1    17 0.422     1 ns          
## 3 omission_r… Light  Vigor…    18    18  1.01e-15    17 1         1 ns

*CV RT

## ANOVA Table (type III tests)
## 
##   Effect DFn DFd     F     p p<.05   ges
## 1   Cond   2  34 2.621 0.087       0.051
## # A tibble: 3 × 10
##   .y.   group1  group2      n1    n2 statistic    df     p p.adj p.adj.signif
## * <chr> <chr>   <chr>    <int> <int>     <dbl> <dbl> <dbl> <dbl> <chr>       
## 1 CV_RT Control Light       18    18      1.20    17 0.246 0.738 ns          
## 2 CV_RT Control Vigorous    18    18      2.20    17 0.042 0.125 ns          
## 3 CV_RT Light   Vigorous    18    18      1.13    17 0.275 0.825 ns

2.) Assumption Verification

*dprime

##       Cond variable statistic          p
## 1  Control   dprime 0.8971030 0.05116676
## 2    Light   dprime 0.9457116 0.36175115
## 3 Vigorous   dprime 0.9419760 0.31313586
## Levene's Test for Homogeneity of Variance (center = median)
##       Df F value Pr(>F)
## group  2  0.2469 0.7822
##       51

*Criterion

##       Cond  variable statistic         p
## 1  Control criterion 0.9362474 0.2496984
## 2    Light criterion 0.9637425 0.6751546
## 3 Vigorous criterion 0.9275668 0.1759388
## Levene's Test for Homogeneity of Variance (center = median)
##       Df F value Pr(>F)
## group  2  1.1334 0.3299
##       51

*Commission Rate

##       Cond        variable statistic          p
## 1  Control commission_rate 0.9129409 0.09695558
## 2    Light commission_rate 0.9176046 0.11724118
## 3 Vigorous commission_rate 0.9313985 0.20549099
## Levene's Test for Homogeneity of Variance (center = median)
##       Df F value Pr(>F)
## group  2  1.4729 0.2389
##       51

*Omission Rate

##       Cond      variable statistic               p
## 1  Control omission_rate 0.4091816 0.0000001433315
## 2    Light omission_rate 0.7224223 0.0001473112217
## 3 Vigorous omission_rate 0.7795962 0.0007933692239
## Levene's Test for Homogeneity of Variance (center = median)
##       Df F value Pr(>F)
## group  2  0.6207 0.5416
##       51

*CV RT

##       Cond variable statistic         p
## 1  Control    CV_RT 0.9400147 0.2899536
## 2    Light    CV_RT 0.9160026 0.1098295
## 3 Vigorous    CV_RT 0.9230854 0.1466036
## Levene's Test for Homogeneity of Variance (center = median)
##       Df F value Pr(>F)
## group  2  0.0426 0.9584
##       51

4.) Transformation/Outlier Removal

-Transformed omission rate (due to non-normality) -Checked for outliers

## [1] 5.582044
## [1] 0.9177454
## [1] NaN
## [1] 1.650815
## [1] 5.579035
## [1] 0.667746
## $Sub_ID
## integer(0)
## 
## $Sub_ID
## integer(0)
## 
## $Sub_ID
## integer(0)
## 
## $Sub_ID
## integer(0)
## 
## $Sub_ID
## integer(0)

5.) ANOVA/Post-Hoc

*dprime

-No need to re-run as no outliers detected/no violations of ANOVA assumptions.

*Criterion

-No need to re-run as no outliers detected/no violations of ANOVA assumptions.

*Commission Rate

-No need to re-run as no outliers detected/no violations of ANOVA assumptions.

*Omission Rate

-Re-ran after normality improved

## ANOVA Table (type III tests)
## 
##   Effect DFn DFd     F    p p<.05   ges
## 1   Cond   2  34 0.073 0.93       0.002
## # A tibble: 3 × 10
##   .y.         group1 group2    n1    n2 statistic    df     p p.adj p.adj.signif
## * <chr>       <chr>  <chr>  <int> <int>     <dbl> <dbl> <dbl> <dbl> <chr>       
## 1 omission_r… Contr… Light     18    18     0.379    17 0.709     1 ns          
## 2 omission_r… Contr… Vigor…    18    18     0.106    17 0.917     1 ns          
## 3 omission_r… Light  Vigor…    18    18    -0.266    17 0.793     1 ns

*CV RT

-No need to re-run as no outliers detected/no violations of ANOVA assumptions.

6.) Plotting

-ggboxplot utilizes 1.5*IQR as outlier criteria -This means some outliers on the plots do not match our outlier criteria (M +- 3sd) -Noted in figure captions

*dprime

## # A tibble: 3 × 8
##   .y.    group1  group2        p p.adj p.format p.signif method
##   <chr>  <chr>   <chr>     <dbl> <dbl> <chr>    <chr>    <chr> 
## 1 dprime Control Light    0.0204 0.02  0.020    *        T-test
## 2 dprime Control Vigorous 0.0530 0.053 0.053    p = .053 T-test
## 3 dprime Light   Vigorous 0.348  0.35  0.348    ns       T-test

*criterion

*Commission Rate

*Omission Rate

*CV RT

*Saving

Results - Facename Task

-Note, there was an issue with the stimulus presentation for FN task -This hasn’t been reviewed/isn’t published

1.) ANOVA/Post-Hoc

## ANOVA Table (type III tests)
## 
##   Effect  DFn   DFd     F     p p<.05   ges
## 1   Cond 1.46 21.83 0.477 0.567       0.016
## # A tibble: 3 × 10
##   .y.         group1 group2    n1    n2 statistic    df     p p.adj p.adj.signif
## * <chr>       <chr>  <chr>  <int> <int>     <dbl> <dbl> <dbl> <dbl> <chr>       
## 1 Accuracy_R… Contr… Light     16    16    -0.152    15 0.881 1     ns          
## 2 Accuracy_R… Contr… Vigor…    16    16    -0.765    15 0.456 1     ns          
## 3 Accuracy_R… Light  Vigor…    16    16    -1.17     15 0.258 0.774 ns

2.) Assumption Verification

-recall, participants performed near ceiling on this task

##       Cond                 variable statistic           p
## 1  Control Accuracy_Response_Trials 0.8516442 0.014406092
## 2    Light Accuracy_Response_Trials 0.8006635 0.002779345
## 3 Vigorous Accuracy_Response_Trials 0.9269438 0.217977871
## Levene's Test for Homogeneity of Variance (center = median)
##       Df F value  Pr(>F)  
## group  2    2.87 0.06713 .
##       45                  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

3.) Transformation/Outlier Removal

## # A tibble: 0 × 1
## # ℹ 1 variable: Sub_ID <int>
## [1] -1.559713
## [1] -2.082307
## [1] -1.81003
## [1] -1.951025
## [1] -1.89841
## [1] -0.9800115

4.) ANOVA/Post-Hoc

## ANOVA Table (type III tests)
## 
##   Effect DFn DFd     F     p p<.05   ges
## 1   Cond   2  30 0.331 0.721       0.011
## # A tibble: 3 × 10
##   .y.         group1 group2    n1    n2 statistic    df     p p.adj p.adj.signif
## * <chr>       <chr>  <chr>  <int> <int>     <dbl> <dbl> <dbl> <dbl> <chr>       
## 1 transforme… Contr… Light     16    16    0.0301    15 0.976 1     ns          
## 2 transforme… Contr… Vigor…    16    16   -0.577     15 0.573 1     ns          
## 3 transforme… Light  Vigor…    16    16   -1.08      15 0.297 0.891 ns

5.) Plotting

*Accuracy Response Trials

-Significance and data non-transformed here (doesn’t matter as P-Values non-significant for both)

*Saving

Results - Flanker Task

1.) ANOVA/Post-Hoc

## ANOVA Table (type III tests)
## 
##   Effect DFn DFd     F     p p<.05   ges
## 1   Cond   2  34 0.306 0.738       0.005
## # A tibble: 3 × 10
##   .y.         group1 group2    n1    n2 statistic    df     p p.adj p.adj.signif
## * <chr>       <chr>  <chr>  <int> <int>     <dbl> <dbl> <dbl> <dbl> <chr>       
## 1 Age.Correc… Contr… Light     18    18    -0.215    17 0.832 1     ns          
## 2 Age.Correc… Contr… Vigor…    18    18    -1.14     17 0.272 0.816 ns          
## 3 Age.Correc… Light  Vigor…    18    18    -0.465    17 0.648 1     ns

2.) Assumption Verification

##       Cond                     variable statistic          p
## 1  Control Age.Corrected.Standard.Score 0.9527735 0.47016698
## 2    Light Age.Corrected.Standard.Score 0.9505375 0.43351143
## 3 Vigorous Age.Corrected.Standard.Score 0.8669769 0.01587097
## Levene's Test for Homogeneity of Variance (center = median)
##       Df F value Pr(>F)
## group  2  0.0556  0.946
##       51

3.) Transformation/Outlier Removal

-1 sd is 15 so 3d=45 -100 plus and minus 45 is 3 sd

## [1] -0.7015437
## integer(0)
## integer(0)

4.) ANOVA/Post-Hoc

-No need to re-run as not severely skewed/no violation Levene’s test.

5.) Plotting

*Age Corrected Standard Scores

*Saving Plot

Results - Cortisol

1.) Exploration

-Participants provided three samples (pre-exercise, post-exercise, end of appt)

-2 data forms cleaned and explored: Absolute (T1, T2, T3) Relative (T2-T1, T3-T1, T3-T2)

2.) Plotting

*individual lines

*suplemental appendix draft (with error bars)

*suplemental appendix (actual)

3.) ANOVA/Post-Hoc

## ANOVA Table (type III tests)
## 
##           Effect  DFn   DFd      F        p p<.05   ges
## 1      timepoint 1.50 23.98 12.929 0.000428     * 0.059
## 2           Cond 2.00 32.00  0.878 0.426000       0.015
## 3 timepoint:Cond 2.75 44.05  1.372 0.264000       0.007
## # A tibble: 9 × 11
##   Cond     .y.      group1    group2    n1    n2 statistic    df       p   p.adj
## * <chr>    <chr>    <chr>     <chr>  <int> <int>     <dbl> <dbl>   <dbl>   <dbl>
## 1 Control  cortisol cortisol… corti…    17    17  -0.00982    16 9.92e-1 9.92e-1
## 2 Control  cortisol cortisol… corti…    17    17   4.68       16 2.54e-4 2.54e-4
## 3 Control  cortisol cortisol… corti…    17    17   2.88       16 1.1 e-2 1.1 e-2
## 4 Light    cortisol cortisol… corti…    17    17   2.43       16 2.7 e-2 2.7 e-2
## 5 Light    cortisol cortisol… corti…    17    17   4.12       16 8.03e-4 8.03e-4
## 6 Light    cortisol cortisol… corti…    17    17   4.58       16 3.1 e-4 3.1 e-4
## 7 Vigorous cortisol cortisol… corti…    17    17  -0.644      16 5.29e-1 5.29e-1
## 8 Vigorous cortisol cortisol… corti…    17    17   1.30       16 2.11e-1 2.11e-1
## 9 Vigorous cortisol cortisol… corti…    17    17   2.13       16 4.9 e-2 4.9 e-2
## # ℹ 1 more variable: p.adj.signif <chr>

4.) Assumption Verification

##       Cond   timepoint variable statistic           p
## 1  Control cortisol_t1 cortisol 0.9613664 0.657293055
## 2  Control cortisol_t2 cortisol 0.8307220 0.005525197
## 3  Control cortisol_t3 cortisol 0.9689943 0.800581219
## 4    Light cortisol_t1 cortisol 0.9343070 0.256702691
## 5    Light cortisol_t2 cortisol 0.9149377 0.121239384
## 6    Light cortisol_t3 cortisol 0.9163350 0.128023258
## 7 Vigorous cortisol_t1 cortisol 0.9750651 0.899415419
## 8 Vigorous cortisol_t2 cortisol 0.9533288 0.511243184
## 9 Vigorous cortisol_t3 cortisol 0.9449839 0.382146307
## Levene's Test for Homogeneity of Variance (center = median)
##        Df F value Pr(>F)
## group   8  1.4037 0.1997
##       144

5.) ANOVA/Post-Hoc

## ANOVA Table (type III tests)
## 
##           Effect  DFn   DFd      F     p p<.05   ges
## 1      timepoint 1.33 19.90 11.394 0.002     * 0.055
## 2           Cond 2.00 30.00  1.704 0.199       0.030
## 3 timepoint:Cond 2.35 35.28  1.849 0.167       0.007
## # A tibble: 9 × 11
##   Cond     .y.      group1    group2    n1    n2 statistic    df       p   p.adj
## * <chr>    <chr>    <chr>     <chr>  <int> <int>     <dbl> <dbl>   <dbl>   <dbl>
## 1 Control  cortisol cortisol… corti…    16    16     3.36     15 4   e-3 4   e-3
## 2 Control  cortisol cortisol… corti…    16    16     4.57     15 3.67e-4 3.67e-4
## 3 Control  cortisol cortisol… corti…    16    16     3.69     15 2   e-3 2   e-3
## 4 Light    cortisol cortisol… corti…    16    16     2.08     15 5.5 e-2 5.5 e-2
## 5 Light    cortisol cortisol… corti…    16    16     3.86     15 2   e-3 2   e-3
## 6 Light    cortisol cortisol… corti…    16    16     4.28     15 6.64e-4 6.64e-4
## 7 Vigorous cortisol cortisol… corti…    16    16    -0.900    15 3.82e-1 3.82e-1
## 8 Vigorous cortisol cortisol… corti…    16    16     1.09     15 2.91e-1 2.91e-1
## 9 Vigorous cortisol cortisol… corti…    16    16     2.02     15 6.2 e-2 6.2 e-2
## # ℹ 1 more variable: p.adj.signif <chr>